varying results: local VS cluster

[Lydia Ickler]

Hi all,

I have an issue regarding execution on 1 machine VS 5 machines.
If I execute the following code the results are not the same though I would 
expect them to be since the input file is the same.
Do you have any suggestions?

Thanks in advance!
Lydia
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
env.getConfig().setGlobalJobParameters(parameters);

//read input file
DataSet<Tuple3<Integer, Integer, Double>> matrixA = readMatrix(env, 
parameters.get("input"));
//Approximate EigenVector by PowerIteration
//get initial vector - which equals matrixA * [1, ... , 1]
DataSet<Tuple3<Integer, Integer, Double>> initial0 = 
(matrixA.groupBy(0)).sum(2);
DataSet<Tuple3<Integer, Integer, Double>> maximum = initial0.maxBy(2);
//normalize by maximum value
DataSet<Tuple3<Integer, Integer, Double>> initial= 
(initial0.cross(maximum)).map(new normalizeByMax());

//BulkIteration to find dominant eigenvector
IterativeDataSet<Tuple3<Integer, Integer, Double>> iteration = 
initial.iterate(1);

DataSet<Tuple3<Integer, Integer, Double>> intermediate = 
((((((matrixA.join(iteration).where(1).equalTo(0))
        .map(new ProjectJoinResultMapper())).groupBy(0, 
1)).sum(2)).groupBy(0)).sum(2)).
        cross(((((((((matrixA.join(iteration).where(1).equalTo(0))
                .map(new ProjectJoinResultMapper())).groupBy(0, 
1)).sum(2))).groupBy(0)).sum(2)).sum(2)))
        .map(new normalizeByMax());

DataSet<Tuple3<Integer, Integer, Double>> diffs = 
(iteration.join(intermediate).where(0).equalTo(0)).with(new deltaFilter());
DataSet<Tuple3<Integer, Integer, Double>> eigenVector  = 
iteration.closeWith(intermediate,diffs);

eigenVector.writeAsCsv(parameters.get("output"));
env.execute("Power Iteration");